Single-cell RNA-seq transcriptomic landscape of human and mouse islets and pathological alterations of diabetes

Kai Chen; Junqing Zhang; Youyuan Huang; Xiaodong Tian; Yinmo Yang; Aimei Dong

doi:10.1016/j.isci.2022.105366

Single-cell RNA-seq transcriptomic landscape of human and mouse islets and pathological alterations of diabetes

iScience. 2022 Oct 14;25(11):105366. doi: 10.1016/j.isci.2022.105366. eCollection 2022 Nov 18.

Authors

Kai Chen¹, Junqing Zhang², Youyuan Huang², Xiaodong Tian¹, Yinmo Yang¹, Aimei Dong²

Affiliations

¹ Department of General Surgery, Peking University First Hospital, Beijing 100034, China.
² Department of Endocrinology, Peking University First Hospital, Beijing 100034, China.

Abstract

Single-cell RNA sequencing has paved the way for delineating the pancreatic islet cell atlas and identifying hallmarks of diabetes. However, pathological alterations of type 2 diabetes (T2D) remain unclear. We isolated pancreatic islets from control and T2D mice for single-cell RNA sequencing (scRNA-seq) and retrieved multiple datasets from the open databases. The complete islet cell landscape and robust marker genes and transcription factors of each endocrine cell type were identified. GLRA1 was restricted to beta cells, and beta cells exhibited obvious heterogeneity. The beta subcluster in the T2D mice remarkably decreased the expression of Slc2a2, G6pc2, Mafa, Nkx6-1, Pdx1, and Ucn3 and had higher unfolded protein response (UPR) scores than in the control mice. Moreover, we developed a Web-based interactive tool, creating new opportunities for the data mining of pancreatic islet scRNA-seq datasets. In conclusion, our work provides a valuable resource for a deeper understanding of the pathological mechanism underlying diabetes.

Keywords: Biological sciences; Diabetology; Endocrinology; Transcriptomics.